Relay Coded Multi-User Cooperative Communications for Uplink 4G Wireless Networks

ABSTRACT

Source nodes in an International Mobile Telecommunications (IMT)-advanced 4G network transmit data on uplink channels to a relay node and a BS using a channel code. The relay node decodes independently the data received from each source node, and applies network coding to data correctly decoded, and transmits the encoded data to the BS. The BS decodes the encoded data transmitted by the sources nodes and the relay nodes cooperatively via a turbo decoding process. The data from each source node are decoded by soft-input soft-output single user decoders and are decoded, together with the data from the relay node, by a soft-input soft-output multi-user decoder.

FIELD OF THE INVENTION

This invention relates generally wireless relay networks, and moreparticularly to uplink in 4G wireless networks communication networksincluding the IMT-Advanced networks.

BACKGROUND OF THE INVENTION

IMT-Advanced 4G Wireless Communication Networks

International Mobile Telecommunications (IMT)-advanced networks are thelatest effort in International Telecommunication Union (ITU)-R for 4Gwireless communications. One goal is to provide an uplink peak spectrumefficiency of 15 bits per second (bps) per Hz, and throughput as high aspossible in the edge area of a network cell, given a reasonable networkcomplexity. To achieve this goal, various enabling technologies havebeen described. A current consensus is to use relay stations (RS) forthe improvement of link performance.

The IEEE802.16j standard has also adopted RS. This invention isparticularly related to the uplink of 4G wireless communication networkswhere the RS is used.

Relay and Network Encoding

Relay-based communications facilitates the cooperative decoding at areceiver to improve an overall link performance. There are in generaltwo types of relay-based communication: amplifying and forwarding (AF)and decoding and forwarding (DF). The invention uses the DF. In networkencoding, the network is modeled as a graph, where edges representchannels from a transmitter to a receiver. Using the max-flow min-cuttheorem, it is possible to calculate the maximum amount of informationflow that can be transmitted from a source to a specific receiver.Network coding can enable all intended receivers to get the maximumnetwork information flow from the source simultaneously. Networkencoding and channel coding both use operations in finite fields.

Cooperative Communications

One purpose of cooperative communication is to provide multiple links orchannels for the communication between a source and destination node sothat a virtual multiple-input multiple-out (MIMO) communications isprovided for encoding and diversity.

Turbo Decoding of Network Encoding and Channel Encoding

In wireless communications, the data transmitted from the source to thedestination are usually channel encoded to reduce the effect of channelnoise. Channel encoding uses a forward error correction (FEC) code, andoften with bit interleaving. The channel code is used to protect thetransmitted data in the presence of noise. After data from one sourcenode is received at the destination, the decoding of the received datato recover the source information can be carried out independent of thedecoding of data from other source nodes. In the case of network coding,because all data are network encoded at the RS, decoded information ofcurrent data can be used to improve the decoding of other data. As aresult, a turbo decoding process can be built up so that the decodingalternates between the channel decoding (single-user decoders) andnetwork decoding (multi-user decoder).

SUMMARY OF THE INVENTION

The embodiments of this invention provide a multi-user, cooperativecommunication network and method which is related to transmitting datafrom multiple source nodes to a destination node with the assistance ofrelay nodes.

This invention is specifically appropriate for the up-link IMT-advanced4G wireless communication networks. One embodiment describes theencoding at the relay node, and another the cooperative decoding processat the destination node.

Source nodes or mobile station (MS) concurrently transmit data usingdifferent wireless channels. The data can be received at a relay nodeand a destination node or base station (BS). The received data can becorrupted by channel fading and noise. The case where the destination isunable to receive or recover all of the data, due to a large distance ornoisy channel condition, is also described.

After the relay node receives the data from multiple sources, the relaydemodulates and decodes the data for each source because channelencoding is applied by each source.

If the data are correctly decoded, which can be determined by a cyclicredundancy check (CRC) codes, then the data are network encoded using amatrix, with an appropriate size, which is invertible over a binaryfinite field. The encoding process does not alter the size of the databefore and after encoding due to features of a full rank of the matrix.

Then, the encoded data are modulated and relayed to the destination. Thesteps include:

-   -   Demodulating and decoding data of individual source nodes;    -   Selecting a number of sources for cooperation;    -   Using an invertible matrix over a finite field for the network        encoding data of the multiple sources; and    -   Transmitting the encoded data to the destination.

At the destination, two data sets can be received. One data set istransmitted by the sources using channel coding, and received directlyby the destination, although corruption is possible. The other data setis transmitted by the relay using network encoding. This data can alsobe corrupted. The destination applies iterative decoding to the receiveddata sets, alternating between a number of single-user decoders and amulti-user decoder.

Components

Soft-In Soft-Out Decoding

For the soft-in soft-out decoding, the destination receives data and apriori information of symbols in the transmitted data. The decodergenerates log-likelihood ratio (LLR) of the received symbols. Thisdecoding is also called maximum a posteriori probability (MAP) decoding.

Information-Exchange-Based Iterative Decoding

Iterative decoding alternates between a multi-user decoder, whichcorresponds to the network encoder, a set of single-user decoders, whichcorrespond to channel encoders.

The embodiments of the invention provide a novel network encodingmatrices, which are invertible over a binary finite field. As a result,self-recovery of the original data transmitted from each source ispossible based on the encoded data in a communication network wheredirect links between sources and the destination are not available, ortoo noisy.

The cooperative communication according to embodiments of the inventionhas the following advantages. Cooperation is considered concurrently formultiple sources using the network encoding in the relay. Therefore, inthis invention, the decoding results of data transmitted from one sourcenode can be exploited for the detection and decoding of data transmittedfrom other source nodes.

Because the data from multiple sources are also decoded at the relay,and then network encoded before the encoded data are transmitted to thedestination, the decoding of the data for multiple sources is alsoenabled at the destination. As a result, there are two types of encodingand decoding in this invention: channel encoding for single sources, andnetwork encoding for multiple sources.

The data recovery process at the destination is to find an estimate ofthe source data of the multiple sources so that the encoded data, afterboth types of encoding processes, have the minimum distance from datareceived at the destination. This maximum-likelihood decoding is knownas a NP problem. In this invention, a near optimal turbo decodingstrategy is provided at the destination to iteratively decode thereceived data.

Network encoding makes it possible to achieve a data transmission rateapproaching the capacity limit. One embodiment applies an exclusively OR(XOR) to data received from two mobile stations (MS) before beingrelaying the data to the BS. This way, the BS can jointly decode thedata from the MS and RS with a lower bit error rate (BER) than if thedata were decoded independently.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow diagram of signaling in a wireless relay network ofmultiple source nodes communicating with a destination node according toembodiments of the invention;

FIG. 2 is a schematic of example uplinks in an IMT-Advanced networkswith four cooperating sources according to embodiments of the invention;

FIG. 3A is a flow diagram of operation at a relay node according toembodiments of the invention;

FIG. 3B is a block diagram of invertible matrices over a binary finitefield according to embodiments of the invention;

FIG. 4 is a block diagram of source and parity data according toembodiments of the invention;

FIG. 5 is a block diagram of a turbo decoder according to embodiments ofthe invention; and

FIG. 6 is a block diagram of a soft-in soft-out decoder according toembodiments of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 1 shows the general signaling in a wireless network of source nodes101, relay nodes 103 and a destination node 106 according to embodimentsof our invention via channels (links) 102, 103 and 104. The sourceconcurrently transmits data to destination, either directly, indirectlyvia the relay nodes. As defined herein, source nodes, users and mobilestations (MS) are equivalent, destination node, base stations (BS) areequivalent, and links and channels are equivalent.

FIG. 2 shows an example network of uplinks in an International MobileTelecommunications (IMT)-advanced wireless communication network whereina relay is used to assistant with the communication. In this example,there are four MSs transmitting signals to the BS concurrently. The MSstransmit symbols “a”, “b”, “c”, “d”, respectively, at a specific timeinstant. Both the BS and the RS can receive the transmission.

The RS decodes the symbols, and uses network encoding to convertcorrectly decoded symbols “a”, “b” “c” “d” to symbols “p₁” “p₂” “p₃”“p₄,” which are then transmitted to the BS.

The correct decoding of a specific MS is not required at RS. As long asthe RS has correctly decoded data from a number of MS, the data can beswitched to a mode of cooperative communication. A transfer matrix, ofan appropriate size, is applied to the data from these MSs. If data fromone MS are incorrectly decoded by the RS, then a different operation canbe followed for this MS.

The indices of the network encoded MSs are included in the head of aframe carrying the data. The number of MS that are network encoded canbe different from frame to frame based on the number of MSs that arecommunicating with the BS, and the number of MS whose data are correctlydecoded at the RS, detected by cyclic redundancy check (CRC) codes.

FIG. 3A shows the method steps performed at the RS. The data transmittedby the MS 301 are decoded 302 independently. Each decoding isindividually checked 303 for correctness. If correct, then the data arenetwork encoded 305 and cooperatively transmitted to the BS 306.Otherwise, some other operations 304 can be applied to the incorrectlydecoded data.

For example, a retransmission strategy can be initiated in 304 so thatthe data that are incorrectly decoded in a current time slot can becorrectly decoded and cooperated with data from other MSs in a latertime slot.

Alternatively, the RS can switch from the DF mode to the AF mode forthis specific MS. As a result, this specific MS does not participate inthe cooperative communications with other MSs, but still retains somedegree of diversity due to the existence of multiple links including thedirect link between the MS and the BS, and the link between the RS andthe BS.

FIG. 3B shows the transfer matrices 311,312 and 313 according toembodiments of the invention, respectively for when K is even, odd or 2.Because the different types of modulation can always be represented atthe bit level, we describe the following by assuming a binarytransmission, i.e., binary phase shift keying (BPSK) for each MS.

The number of MS for cooperative communications can change from frame toframe. For one frame there are “K” MSs, where “K” can be even 311 or odd312. The data from the “K” MSs, i.e., a column vector “D” with “K”symbols at a specific time index, is network encoded using a transfermatrix “A”, and generate a column vector “P” to be transmitted from theRS to the BS. That is, P=AD.

Invertible Matrix

The matrix is designed based on two objectives.

First, self-recovery capability must be guaranteed, i.e., the columnvector “D” can be correctly decoded even though only “P” is available.This is required in some cases where the direct links between the MSsand the BS are too severe to carry data. Therefore, the matrix “A” is afull rank, non-singular square matrix, i.e., an invertible matrix over afinite field. In linear algebra, an n-by-n square matrix A isinvertible, or non-singular if there exists an n-by-n matrix B such thatAB=BA=I_(n), where I_(n) denotes the n-by-n identity matrix and themultiplication used is conventional. If this is the case, then thematrix B is uniquely determined by the matrix A, and is called theinverse of A, or A⁻¹.

Second, information of one symbol is spread over the encoded symbols sothat soft information can be extracted later at the BS for the turbodecoding. The size of the matrix “A” is arbitrary, and the case when“K”=2 is described specifically in FIG. 3. B. Permutation of rows of thematrix gives the equivalent result.

Channel encoding and decoding is used for the data of each MS to dealwith errors. As a result, the data transmitted each MS also includesparity information. Because any linear channel code can be converted toa network code, we describe the data 401 in FIG. 4 from each MS as“x_(i),” i.e., source information, and “x_(i) ^(p),” i.e., parityinformation, i=1, . . . , K.

If the RS has correctly decoded the data, then the RS encodes the data401 from “K” MS via network encoding. The network encoded data aredenoted as 402, where N is the number of symbols in a frame. Inaddition, when all MSs are using the identical channel code, data 402are in the identical coding space of the channel code. Therefore, data402 can also be channel decoded in the horizontal direction as shown inFIG. 4.

BS Decoder

FIG. 5 shows the decoder at the BS. The destination (BS) receivessignals from both the MSs and the RS, which can be corrupted by channelfading and noise. The objective of the BS is to recover the source datatransmitted by each MS, i.e., “x_(i)”, i=1, . . . , K, in FIG. 4.

The optimal solution uses Maximum Likelihood (ML) decoding, which givesan estimate X* based on which the data Y* generated after both channelencoding and network encoding has the minimum distance from the entirereceived signal at the BS. The turbo decoding structure shown in FIG. 5provides the near optimal solution of this problem.

Data 501 is received directly from the MS and data 502 is received fromthe RS. The data can be corrupted due to channel fading and noise.

The decoder includes multiplexers 503-505, and demultiplexer 506.Multiplexing is used to combine data received from the set of source andthe relay for a multi-user decoder 510. Demultiplexing is used toseparate the decoded data from the multi-user decoder for a set ofsingle-user decoders 511-512, one for each user. Each of the decoders511-512 is a soft-in-soft-out decoder, which implements a maximum aposteriori probability decoding, or equivalent.

Threshold detectors 521-522 output 1 when the input is larger than 0,and −1 otherwise.

FIG. 6 shows a soft-in-soft-out decoder 511 that has two inputs 601-602.One input is the received signal from the channel output at the BS, andthe other is a priori information of the symbols that are extracted fromthe multi-user decoder. The input symbols are the channel corruptedversion of the encoded data. Each symbol has a priori information. Theoutput log-likelihood ratio (LLR) is generated for each input symbol. Asa result, both source symbols and parity symbols have the a prioriinformation before decoding, and the LLR and extrinsic information afterdecoding

When the MS in cooperation use identical channel code, FIG. 6 also showsthe structure of the multi-user decoder. When the MS in cooperation usedifferent channel codes, FIG. 6 shows the structure of the multi-userdecoder except that the a priori information 602, LLR 603 and extrinsicinformation 604 are only available for the source symbols, but not forthe network coded symbol, in the network coding

The output 603 of this decoder includes a hard decision 606, which is aLLR of decoded symbols. The LLR value less the input and a prioriinformation 602 is called extrinsic information 604, which is the newinformation generated by the decoder. The extrinsic information ispassed between the single-user decoders and multi-user decoder, afterde-multiplexing or multiplexing as the updated a priori information toform a loop for turbo decoding. Finally, threshold detection withrespect to value “0” is the hard decision of decoded symbols.

EFFECT OF THE INVENTION

In an example network, four MSs perform cooperative communications. Forthe example, recursive systematic convolutional (RSC) code withgenerator (7,5)_(oct) and rate ½ is used as the channel encode for eachMS. Each MS-BS link experiences different block fading, which isequivalent to using different Gaussian channels. Operation at the RS isa 4×4 matrix, which generates coded data equivalent to the parityinformation of a (8,4,4) extended Hamming code.

When channel coding is not considered, for SNR_(d)=5 dB of the linkbetween the MS and the BS, there is a 2 dB improvement at BER=10⁻⁴ forvarious SNR of links between the RS and the BS, compared with maximumratio combining (MRC) diversity. This results shows that when moderatedirect links between MSs and BS exist, large gain can be obtained withthe network encoding at the RS, even without the iterative decodingbetween channel encoding and network encoding.

When channel coding is consider, for SNR_(d)=1 dB of the link betweenthe MS and the BS, there is about 3 dB improvement at BER=10⁻⁴ forvarious SNR of links between the RS and the BS, compared with MRCdiversity. This results shows significant gain can be obtained withiterative decoding in the invention.

Although the invention has been described by way of examples ofpreferred embodiments, it is to be understood that various otheradaptations and modifications may be made within the spirit and scope ofthe invention. Therefore, it is the object of the appended claims tocover all such variations and modifications as come within the truespirit and scope of the invention.

1. A wireless International Mobile Telecommunications (IMT)-advanced 4Gnetwork including a set of source nodes, wherein the set of source nodestransmit data on uplink channels using a channel code, comprising: arelay node comprising: a receiver; a set of decoders, there being onedecoder for each source node transmitting the data, and wherein the dataare channel encoded, and wherein each decoder determines whether thedata received from the source node are decoded correctly; a networkencoder configured to encode the data correctly decoded, wherein eachnetwork encoder uses an invertible matrix over a binary finite field toencode the correctly decoded data; and a transmitter configured totransmit the network encoded data.
 2. The network of claim 1, furthercomprising: a destination node comprising: a receiver; a multiplexerconfigured to combine the channel encode data transmitted by the set ofsources and the network encoded data transmitted by the relay amulti-user decoder configured to decode the network encoded data; ademultiplexer configured to separate the combined data according to eachsource to produce decode data for each source; a set of soft-inputsoft-output decoders, there being one soft-input soft-output for eachseparate decoded data; and a threshold detector, for each soft-inputsoft-output decoder, configured to produce a hard decision for eachsoft-input soft-output decoder.
 3. The network of claim 1, wherein theset of source nodes transmit concurrently, using channel codes.
 4. Thenetwork of claim 1, wherein data from each source node are channeldecoded and a correctness of the decoding is determined.
 5. The networkof claim 2, wherein each soft-input soft-output decoder is a single-userdecoder that produces a priori information for the multi-user decoder.6. The network of claim 2, wherein the soft-input soft-output decoder isa multi-user decoder that produces a priori information for thesingle-user decoders.
 7. The network of claim 5, wherein each soft-inputsoft-output single user decoder receives a priori information from themulti-user decoder, and wherein the a priori information is subtractedfrom a log-likelihood ratio to produce extrinsic information to act asthe a priori information for the multi-user decoder.
 8. The network ofclaim 6, wherein the soft-input soft-output multi-user decoder receivesa priori information from the single user decoders, and wherein thepriori information is subtracted from a generated log-likelihood ratioto produce extrinsic information to act as the a priori information forthe single-user decoders.
 9. The network of claim 2, wherein the soft-insoft-out multi-user decoding and the soft-input soft-output single-userdecoding alternate iteratively with information exchange.
 10. Thenetwork of claim 1, wherein the source nodes use an identical channelcode and the data are network encoded at the relay node for cooperation.11. The network of claim 1, wherein the source nodes use differentchannel codes and the data are network encoded at the relay node forcooperation.
 12. The network of claim 2, wherein when cooperative sourcenodes have an identical channel code, and the data are channel decodedwith the same soft-in soft-out single user decoder after networkencoding.
 13. The network of claim 9, wherein the extrinsic informationis extracted from the received data for systematic and parity data usinga priori information.
 14. The network of claim 1, further comprising:means for enabling the source nodes to join in the cooperativetransmitting.
 15. A method for communicating in a wireless InternationalMobile Telecommunications (IMT)-advanced 4G network including a set ofsource nodes, a relay node and a base station, wherein the set of sourcenodes transmit data on uplink channels to the relay node and the BSusing a channel code, comprising: decoding independently, in the relaynode, for each source node, the data that are channel coded; applyingnetwork coding to the data that are correctly decoded; transmitting thenetwork encoded data to the BS; and decoding in the base station, thedata that are channel coded by each source nodes using a set ofsingle-user decoders, and decoding the data that are network encoded bythe relay station using a multi-user decoder.
 16. The method of claim15, wherein the network encoding uses an invertible matrix over a binaryfinite field.
 17. The method of claim 15, wherein the set of sourcenodes transmit concurrently.
 18. The method of claim 15, wherein eachsingle-user decoder and the multi-user decoder use maximum a posterioriprobability decoding.